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BEGIN:VEVENT
DTSTAMP:20260402T113226
DTSTART;TZID=America/Detroit:20260410T120000
DTEND;TZID=America/Detroit:20260410T133000
SUMMARY:Lecture / Discussion:Exploring Non-Linear Career Paths
DESCRIPTION:CEW+ and WISE are pleased to host University of Michigan engineering alumna Lindsey Kilbride\, who will share valuable insight on navigating career uncertainty\, embracing change\, and finding meaningful work beyond traditional pathways. This session will explore how to make intentional career choices\, leverage transferable skills\, and build a professional life that evolves alongside personal interests and priorities. \n\nAfter earning her degree in industrial and operations engineering\, Lindsey began a career that took unexpected and rewarding turns\, ultimately leading her to work far outside her original field of study. Through multiple transitions\, she learned how to apply her analytics and data science skills across new fields and roles that better aligned with her values\, strengths\, and interests. Her journey underscores the importance of adaptability\, continuous learning\, and the confidence to pursue non-linear career paths. Alongside her professional growth\, Lindsey has navigated career change while raising a family\, offering an honest perspective on balancing competing priorities\, setting boundaries\, and redefining success over time. Her experience reflects the challenges many students will encounter and offers practical insight into building a fulfilling\, sustainable career in a changing workforce.
UID:145657-21897642@events.umich.edu
URL:https://events.umich.edu/event/145657
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:Center for the Education of Women
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20250904T153242
DTSTART;TZID=America/Detroit:20260416T110000
DTEND;TZID=America/Detroit:20260416T120000
SUMMARY:Social / Informal Gathering:Weekly coffee chat hosted by INFORMS & HFES
DESCRIPTION:Come join us in the IOE Commons for some coffee and networking!
UID:138834-21896908@events.umich.edu
URL:https://events.umich.edu/event/138834
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Industrial and Operations Engineering Building - Community Suite, Room 1700
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260330T113817
DTSTART;TZID=America/Detroit:20260416T150000
DTEND;TZID=America/Detroit:20260416T160000
SUMMARY:Lecture / Discussion:IOE 899:  Kapil Chalil Madathil
DESCRIPTION:As work\, healthcare\, and decision-making increasingly occur across distance\, physical separation is often assumed to degrade performance. Research in human-centered systems design reveals a more nuanced reality: performance often survives distance\, but the hidden costs shift to workload\, and coordination. This talk examines how the design of collaborative systems determines whether distance becomes manageable or dangerous. Drawing on two decades of research spanning remote collaboration\, immersive virtual environments\, telemedicine-enabled stroke care\, and human-AI teaming in high-risk settings\, the talk shows how redesigning systems\, rather than pushing people harder\, can dramatically improve outcomes. The talk argues that the future of distributed work and intelligent systems will be defined by seamlessly integrated\, intelligently designed human–machine partnerships.
UID:147209-21900527@events.umich.edu
URL:https://events.umich.edu/event/147209
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Industrial and Operations Engineering Building - 1680
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260331T141558
DTSTART;TZID=America/Detroit:20260416T153000
DTEND;TZID=America/Detroit:20260416T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series -  From Market Signals to Maintenance Decisions: Electricity Price Forecasting and Market-Aware Maintenance for Energy Assets
DESCRIPTION:Abstract:\nOperational decision-making in modern power systems is increasingly shaped by uncertain market signals\, such as electricity prices and curtailment levels. In this talk\, I will present our research group’s recent efforts to develop data- driven methods for forecasting these signals\, and further leveraging them to inform asset-level decision-making. First\, I will present a multivariate statistical approach for electricity price forecasting designed to capture system\, market\, and temporal dependencies that are prevalent in electricity price signals. The proposed approach is evaluated on two years of electricity prices from the California Independent System Operator\, showing significant improvements in both point and probabilistic forecast metrics relative to well-established statistical and emerging deep learning methods. Independent validation against industry-adopted forecasting systems further demonstrates the approach’s competitive performance and practical relevance. I then turn to how variability in market signals (naturally viewed as a challenge for asset management) can\, counter-intuitively\, be turned into an opportunity for improved decision-making. In particular\, I will present a grid- informed maintenance optimization framework for wind energy assets that incorporates grid- level information\, such as electricity prices and curtailment\, to support condition-based maintenance decisions. Together\, these results highlight how market signals can be accurately predicted\, and further leveraged to inform asset management\, bridging forecasting and optimization in modern power systems.\n\nBiography:\nAziz Ezzat is an Assistant Professor of Industrial & Systems Engineering at Rutgers University\, where he leads the Renewables & Industrial Analytics (RIA) Research Group. He received his PhD degree in Texas A&M University\, and his BSc. Degree from Alexandria\, Egypt\, both in Industrial & Systems Engineering. Aziz’s research develops data science\, AI\, and machine learning methods for energy\, environmental\, and industrial systems\, with support from the National Science Foundation\, U.S. Department of Energy\, the state of New Jersey\, and industry partners. His work has appeared in leading journals such as Technometrics\, Annals of Applied Statistics\, IISE Transactions\, and IEEE Transactions on Sustainable Energy. Aziz is a recipient of the A. Walter Tyson Early Career Award\, the IIF-SAS ® Research Methodology Award\, and the Excellence in Teaching Awards from the Operations Research and Data Analytics Divisions of the Institute of Industrial & Systems Engineers (IISE). He served as the 2023-2024 President of the Energy Systems Division of IISE\, where he introduced numerous initiatives to advance the broader impacts of data and decision sciences\, including the inaugural PG&E Energy Analytics Challenge—an industry-sponsored\, national-scale energy forecasting competition. He is a professional member of INFORMS\, IISE\, IEEE\, and IIF. More about his research and teaching can be found at: https://sites.rutgers.edu/azizezzat/.
UID:145470-21897385@events.umich.edu
URL:https://events.umich.edu/event/145470
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:Electrical Engineering and Computer Science Building - 1303
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260130T162411
DTSTART;TZID=America/Detroit:20260417T070000
DTEND;TZID=America/Detroit:20260417T170000
SUMMARY:Conference / Symposium:2026 CCAT Global Symposium on Mobility Innovation presented by Mcity and UMTRI
DESCRIPTION:We are pleased to bring the ninth annual CCAT Global Symposium on Mobility Innovation\, presented by Mcity and University of Michigan Transportation Research Institute (UMTRI)\, to the Morris Lawrence Building at Washtenaw Community College on Friday\, April 17th! This two-track conference will feature a debate\, panel discussion\, and research presentations on the latest issues facing the transportation industry. Learn from experts in academia\, government\, and industry by securing your space now!
UID:144869-21896070@events.umich.edu
URL:https://events.umich.edu/event/144869
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260406T085442
DTSTART;TZID=America/Detroit:20260417T150000
DTEND;TZID=America/Detroit:20260417T183000
SUMMARY:Exhibition:Senior Design Expo
DESCRIPTION:U-M IOE students will showcase their real-world impact at the biannual Senior Design Expo.
UID:145396-21897243@events.umich.edu
URL:https://events.umich.edu/event/145396
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Ford Robotics Building - Atrium
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260409T085630
DTSTART;TZID=America/Detroit:20260421T150000
DTEND;TZID=America/Detroit:20260421T160000
SUMMARY:Social / Informal Gathering:IOE Community Event
DESCRIPTION:Join fellow members of the IOE community for some delicious treats in the Community Suite! Celebrate the last day of classes with ice cream!
UID:142671-21891283@events.umich.edu
URL:https://events.umich.edu/event/142671
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Industrial and Operations Engineering Building - Community Suite (IOE 1700)
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260119T140940
DTSTART;TZID=America/Detroit:20260422T090000
DTEND;TZID=America/Detroit:20260422T151000
SUMMARY:Conference / Symposium:NLP @ Michigan Day 2026
DESCRIPTION:As natural language processing (NLP) continues to advance rapidly\, it is reshaping how machines understand\, generate\, and interact with human beings. Recent progress in large language models\, multimodal systems\, and interactive agents has expanded the impact of NLP across domains such as education\, healthcare\, robotics\, social sciences\, and scientific discovery.\n\nNLP Day @ Michigan 2026 is dedicated to exploring these advances and their broader implications. The event will feature invited talks\, poster presentations\, and roundtable discussions\, bringing together researchers and practitioners to share recent work\, discuss emerging challenges\, and identify future directions in NLP.\n\nNLP Day @ Michigan 2026 will take place on North Campus\, in the Bob & Betty Beyster Building with a poster session in Tishman Hall of the same building\, with details on the schedule to be announced. REGISTRATION IS REQUIRED.\n\nRegistration includes lunch. Current University of Michigan students\, faculty\, and staff may register for the symposium for free.
UID:144112-21894681@events.umich.edu
URL:https://events.umich.edu/event/144112
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:BBB
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20250904T153242
DTSTART;TZID=America/Detroit:20260423T110000
DTEND;TZID=America/Detroit:20260423T120000
SUMMARY:Social / Informal Gathering:Weekly coffee chat hosted by INFORMS & HFES
DESCRIPTION:Come join us in the IOE Commons for some coffee and networking!
UID:138834-21896909@events.umich.edu
URL:https://events.umich.edu/event/138834
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Industrial and Operations Engineering Building - Community Suite, Room 1700
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260423T105736
DTSTART;TZID=America/Detroit:20260430T180000
DTEND;TZID=America/Detroit:20260430T193000
SUMMARY:Social / Informal Gathering:IOE Grad Student Banquet
DESCRIPTION:Come celebrate this academic year and all of our graduate students \n\nBuffet begins at 6:30 PM
UID:142669-21891280@events.umich.edu
URL:https://events.umich.edu/event/142669
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Michigan Union - Anderson Room (1st Floor)
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20251212T162624
DTSTART;TZID=America/Detroit:20260501T160000
DTEND;TZID=America/Detroit:20260501T173000
SUMMARY:Reception / Open House:Undergraduate Graduation Open House
DESCRIPTION:Open house to celebrate the graduation of the undergraduates. The open house will be from 4pm - 5:30pm.
UID:142670-21891281@events.umich.edu
URL:https://events.umich.edu/event/142670
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Industrial and Operations Engineering Building - Community Suite (IOE 1700) & Reflecting Pool.
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260507T085012
DTSTART;TZID=America/Detroit:20260511T130000
DTEND;TZID=America/Detroit:20260511T140000
SUMMARY:Workshop / Seminar:Institute for Energy Solutions & Electric Vehicle Center: Understanding and Development of Sulfide-Based Solid-State Batteries
DESCRIPTION:Abstract: There is a growing interest in low-cost and scalable manufacturing and recycling methods for lithium-ion batteries (LIBs). In this talk\, I will discuss on our recent progress in innovating materials and processing technologies for more sustainable LIBs. I will first discuss our recent work on the next generation direct recycling methods\, aiming to produce new electrode materials capable of matching the performance of native materials. By leveraging advanced characterizations\, we study the microstructure and compositional evolution of battery materials during cycling\, which are compared with the recycled materials. We demonstrate successful recycling of various battery materials to high performance active materials. Scaling up challenges will also be discussed.\n\nBio: Dr. Zheng Chen is a Professor in the Aiiso Yufeng Li Department of Chemical and Nano Engineering\, and Program of Materials Science and Engineering at UC San Diego.  His research group has been mainly focusing on 1) design and synthesis of nanostructured and polymeric materials for energy storage and conversion\, and 2) development of scalable materials manufacturing recycling methods. Dr. Chen has received the 2024 ECS Toyota Young Investigator Fellowship\, 2023 ECS Battery Division Early Career Award\, NASA’s 2018 Early Career Faculty Award\, the LG Chem Global Battery Innovation Contest (BIC) Award in 2018\, and the 2018 ACF PRF New Investigator Award. He has been selected as a Scialog Fellow in Advanced Energy Storage by Research Corporation and as a participant of 2022 Germany-US and 2019 China- America Frontiers of Engineering Symposium (CAFOE)\, National Academy of Engineering.
UID:148092-21902939@events.umich.edu
URL:https://events.umich.edu/event/148092
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:Michigan Memorial Phoenix Project - 2000 PML
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260507T085855
DTSTART;TZID=America/Detroit:20260521T090000
DTEND;TZID=America/Detroit:20260521T100000
SUMMARY:Lecture / Discussion:PhD Defense: Jaeshin Park
DESCRIPTION:Date: May 21\, 2026\nTime: 9:00 AM\nLocation: IOE 2717 + Zoom https://umich.zoom.us/my/jaeshin?omn=95985574553\nChair: Eunshin Byon\nDissertation Title: Data-Driven Uncertainty Quantification for Computer Models and Digital Twins: From Variance Reduction to Real-Time Calibration
UID:146165-21898610@events.umich.edu
URL:https://events.umich.edu/event/146165
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial And Operations Engineering
LOCATION:Industrial and Operations Engineering Building - 2717
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260515T082607
DTSTART;TZID=America/Detroit:20260527T080000
DTEND;TZID=America/Detroit:20260527T180000
SUMMARY:Conference / Symposium:Institute for Energy Solutions 2026 Energy Symposium
DESCRIPTION:The U-M Institute for Energy Solutions hosted its inaugural energy symposium in 2025 themed “What (Energy Issue) Is Keeping You Up at Night?”. The Symposium included faculty\, staff\, and students from across the University and external partners from academia\, industry\, government\, and nonprofits. Our goal was to identify critical energy challenges and discuss innovative energy solutions.\n\nThis year\, on May 27-28\, 2026\, IES is hosting its second energy symposium\, themed “What are your Energy Dreams?”. We want to know what energy challenges and solutions excite (“energize”) you today. Join us to discuss opportunities in electricity grid technology and computation\, biotechnology for energy feedstocks\, critical minerals\, geothermal systems\, data centers\, behavioral challenges in energy\, and more. IES will be welcoming Dr. Benjamin Kroposki\, the Director of the Power Systems Engineering Center at the National Laboratory of the Rockies (NLR)\, to give a plenary at the symposium.\n\nThe event will take place at the Gerald R. Ford Presidential Library (1000 Beal Ave\, Ann Arbor\, MI 48109) on U-M’s North Campus. Further details will be announced soon. Save the date!
UID:148298-21903822@events.umich.edu
URL:https://events.umich.edu/event/148298
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:Gerald Ford Library
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260515T082607
DTSTART;TZID=America/Detroit:20260528T080000
DTEND;TZID=America/Detroit:20260528T170000
SUMMARY:Conference / Symposium:Institute for Energy Solutions 2026 Energy Symposium
DESCRIPTION:The U-M Institute for Energy Solutions hosted its inaugural energy symposium in 2025 themed “What (Energy Issue) Is Keeping You Up at Night?”. The Symposium included faculty\, staff\, and students from across the University and external partners from academia\, industry\, government\, and nonprofits. Our goal was to identify critical energy challenges and discuss innovative energy solutions.\n\nThis year\, on May 27-28\, 2026\, IES is hosting its second energy symposium\, themed “What are your Energy Dreams?”. We want to know what energy challenges and solutions excite (“energize”) you today. Join us to discuss opportunities in electricity grid technology and computation\, biotechnology for energy feedstocks\, critical minerals\, geothermal systems\, data centers\, behavioral challenges in energy\, and more. IES will be welcoming Dr. Benjamin Kroposki\, the Director of the Power Systems Engineering Center at the National Laboratory of the Rockies (NLR)\, to give a plenary at the symposium.\n\nThe event will take place at the Gerald R. Ford Presidential Library (1000 Beal Ave\, Ann Arbor\, MI 48109) on U-M’s North Campus. Further details will be announced soon. Save the date!
UID:148298-21903823@events.umich.edu
URL:https://events.umich.edu/event/148298
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:Gerald Ford Library
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260223T143824
DTSTART;TZID=America/Detroit:20260616T140000
DTEND;TZID=America/Detroit:20260616T150000
SUMMARY:Lecture / Discussion:Rare Failures\, Public Perception\, and Automated Driving: Why Exceptional Events Shape Trust in Emerging Safety Technologies
DESCRIPTION:This lecture explores the “vaccine paradox” of automated driving: why rare\, highly publicized failures of self-driving vehicles provoke intense emotional and political reactions while the far more common harms of human driving remain normalized. Drawing on risk psychology\, public-health history\, and human-factors research\, Prof. McGehee examines how visibility imbalance\, trust\, and perceptions of control shape public acceptance of emerging vehicle automation. Using real-world examples from automated-vehicle deployments alongside lessons from vaccine adoption and safety communication\, the talk argues that societal expectations for perfection in automation may obscure meaningful population-level safety gains. The presentation concludes by discussing how transparency\, responsible system design\, and careful language around driver-assistance technologies can help align public perception with evidence as automated driving evolves toward broader deployment.\n---\nAbout the speaker: Daniel V. McGehee\, is Professor of Industrial and Systems Engineering at the University of Iowa and Director of the Driving Safety Research Institute (DSRI) and the National Advanced Driving Simulator (NADS)\, one of the world’s largest and most advanced ground-vehicle simulation facilities. For more than three decades\, his work has focused on human factors\, driver behavior\, and the safe integration of advanced vehicle technologies\, including automated driving and driver-assistance systems. Dr. McGehee’s research spans engineering\, medicine\, public health\, and transportation policy\, with projects funded by the U.S. Department of Transportation\, National Institutes of Health\, and the automotive industry. He has led over $40 million in sponsored research and authored more than 160 scientific publications addressing driver attention\, crash avoidance\, vulnerable road users\, and the design of vehicle interfaces. His work combines naturalistic driving studies\, simulation\, and field research to better understand how humans interact with emerging mobility systems. At the University of Iowa\, he holds joint appointments in emergency medicine and public health\, reflecting his longstanding interest in traffic safety as a population-level health issue.
UID:145812-21897843@events.umich.edu
URL:https://events.umich.edu/event/145812
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:Transportation Research Institute - Room 139
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260713T090000
DTEND;TZID=America/Detroit:20260713T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901187@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260714T090000
DTEND;TZID=America/Detroit:20260714T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901188@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260715T090000
DTEND;TZID=America/Detroit:20260715T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901189@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260716T090000
DTEND;TZID=America/Detroit:20260716T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901190@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260717T090000
DTEND;TZID=America/Detroit:20260717T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901191@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260720T090000
DTEND;TZID=America/Detroit:20260720T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901194@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260721T090000
DTEND;TZID=America/Detroit:20260721T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901195@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260722T090000
DTEND;TZID=America/Detroit:20260722T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901196@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260723T090000
DTEND;TZID=America/Detroit:20260723T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901197@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260724T090000
DTEND;TZID=America/Detroit:20260724T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901198@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260727T090000
DTEND;TZID=America/Detroit:20260727T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901201@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260728T090000
DTEND;TZID=America/Detroit:20260728T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901202@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260729T090000
DTEND;TZID=America/Detroit:20260729T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901203@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260730T090000
DTEND;TZID=America/Detroit:20260730T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901204@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T104211
DTSTART;TZID=America/Detroit:20260731T090000
DTEND;TZID=America/Detroit:20260731T160000
SUMMARY:Workshop / Seminar:AI for Scientists and Engineers Summer Academy
DESCRIPTION:Academy Overview\nThe AI for Scientists and Engineers Summer Academy is designed for academic researchers\, including university faculty\, in a wide range of domains including biological sciences\, engineering\, environmental and earth science\, physical sciences\, and social sciences. Participants will learn the mathematical foundations of machine learning (ML)\, critically assess the data used in AI models\, evaluate and validate ML model outputs\, and understand strategic considerations for incorporating AI into research workflows. The prerequisites are college level math and statistics\; prior coding experience is not required. Specific topics include supervised and unsupervised learning\, neural networks\, causal inference\, and science-informed machine learning models.\n\nThe Summer Academy consists of three weeks of instructions\, with different focuses. One can choose to attend any or all weeks\; however\, weeks 2 and 3 require some prior knowledge of AI / ML.\n\nWeek 1 (Monday\, July 13 – Friday\, July 17\, 2026): The conceptual understanding of AI and its applications in domain research.\nWeek 2 (Monday\, July 20 – Friday\, July 24\, 2026): The implementation of ML models in a Python environment.\nWeek 3 (Monday\, July 27 – Friday\, July 31\, 2026): Advanced topics of AI and its applications in domain research.
UID:147530-21901205@events.umich.edu
URL:https://events.umich.edu/event/147530
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260423T124348
DTSTART;TZID=America/Detroit:20260917T153000
DTEND;TZID=America/Detroit:20260917T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147937-21902572@events.umich.edu
URL:https://events.umich.edu/event/147937
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260423T124225
DTSTART;TZID=America/Detroit:20260924T153000
DTEND;TZID=America/Detroit:20260924T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147943-21902578@events.umich.edu
URL:https://events.umich.edu/event/147943
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T111546
DTSTART;TZID=America/Detroit:20261001T153000
DTEND;TZID=America/Detroit:20261001T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147944-21902579@events.umich.edu
URL:https://events.umich.edu/event/147944
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T111748
DTSTART;TZID=America/Detroit:20261008T153000
DTEND;TZID=America/Detroit:20261008T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147945-21902580@events.umich.edu
URL:https://events.umich.edu/event/147945
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260423T131611
DTSTART;TZID=America/Detroit:20261015T153000
DTEND;TZID=America/Detroit:20261015T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147946-21902581@events.umich.edu
URL:https://events.umich.edu/event/147946
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T111932
DTSTART;TZID=America/Detroit:20261022T153000
DTEND;TZID=America/Detroit:20261022T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147947-21902582@events.umich.edu
URL:https://events.umich.edu/event/147947
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T112101
DTSTART;TZID=America/Detroit:20261029T153000
DTEND;TZID=America/Detroit:20261029T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract: \n\nBiography:
UID:147948-21902584@events.umich.edu
URL:https://events.umich.edu/event/147948
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260423T132410
DTSTART;TZID=America/Detroit:20261105T153000
DTEND;TZID=America/Detroit:20261105T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147950-21902585@events.umich.edu
URL:https://events.umich.edu/event/147950
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T112210
DTSTART;TZID=America/Detroit:20261112T153000
DTEND;TZID=America/Detroit:20261112T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147951-21902586@events.umich.edu
URL:https://events.umich.edu/event/147951
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T112311
DTSTART;TZID=America/Detroit:20261119T153000
DTEND;TZID=America/Detroit:20261119T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147953-21902590@events.umich.edu
URL:https://events.umich.edu/event/147953
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260423T133549
DTSTART;TZID=America/Detroit:20261203T153000
DTEND;TZID=America/Detroit:20261203T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147954-21902598@events.umich.edu
URL:https://events.umich.edu/event/147954
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260424T112419
DTSTART;TZID=America/Detroit:20261210T153000
DTEND;TZID=America/Detroit:20261210T163000
SUMMARY:Workshop / Seminar:IES Energy Seminar Series
DESCRIPTION:Abstract:\n\nBiography:
UID:147955-21902611@events.umich.edu
URL:https://events.umich.edu/event/147955
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Industrial and Operations Engineering
LOCATION:
CONTACT:
END:VEVENT
END:VCALENDAR